Automated path-based recommendation for risk mitigation

US2025232241A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2025232241-A1
Application numberUS-202519097358-A
CountryUS
Kind codeA1
Filing dateApr 1, 2025
Priority dateAug 22, 2019
Publication dateJul 17, 2025
Grant date

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Abstract

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Systems and methods for automated path-based recommendation for risk mitigation are provided. An entity assessment server, responsive to a request for a recommendation for modifying a current risk assessment score of an entity to a target risk assessment score, accesses an input attribute vector for the entity and clusters of entities defined by historical attribute vectors. The entity assessment server assigns the input attribute vector to a particular cluster and determines a requirement on movement from a first point to a second point in a multi-dimensional space based on the statistics computed from the particular cluster. The first point corresponds to the current risk assessment score and the second point corresponds to the target risk assessment score. The entity assessment server computes an attribute-change vector so that a path defined by the attribute-change vector complies with the requirement and generates the recommendation from the attribute-change vector.

First claim

Opening claim text (preview).

1 . A method in which one or more processing devices of a server system perform operations comprising: receiving, from a user device, a request for a recommendation for modifying a first value of a risk assessment score computed from input attribute values of an entity associated with the user device to a target value of the risk assessment score, the risk assessment score used to control access by a computing device associated with the entity to an interactive computing environment hosted by a host system, wherein the host system is configured to present a first type of interactive user experience to a first type of user group associated with the first value of the risk assessment score and present to a second type of interactive user experience to a second type of user group associated with the target value of the risk assessment score; computing an attribute-change vector indicating a path from (a) a first point that corresponds to the first value of the risk assessment score to (b) a second point that corresponds to the target value of the risk assessment score, wherein computing the attribute-change vector comprises: determining a requirement on movement from the first point to the second point, and selecting the attribute-change vector that complies with the requirement; generating, using the computed attribute-change vector, the recommendation; and transmitting, to the user device, the recommendation in response to the request for the recommendation for use in improving the first value of the risk assessment score to the target value of the risk assessment score which causes the host system to modify a functionality of an online interface by rearranging a layout of the online interface to switch from presenting the first type of interactive user experience to presenting the second type of interactive user experience. 2 . The method of claim 1 , wherein: the path complying with the requirement comprises the path being a shortest path along a surface between the first point and the second point in m-dimensional space. 3 . The method of claim 1 , wherein: the requirement is based on a precision matrix for an associated user group and a mean vector, and the requirement comprises minimizing an objective function subject to a score change constraint that corresponds to the target value of the risk assessment score, the objective function is computed from the precision matrix, the mean vector, and the attribute-change vector. 4 . The method of claim 1 , wherein the requirement is based on a precision matrix for an associated user group and a mean vector; and the requirement comprises maximizing a score change objective function subject to a constraint that is computed from the precision matrix, the mean vector, and the attribute-change vector. 5 . The method of claim 1 , further comprising determining the target value of the risk assessment score by applying a risk assessment function to a sum of an input attribute vector having the input attribute values of the entity, and wherein computing the attribute-change vector further comprises determining that the attribute-change vector further complies with at least one constraint, the at least one constraint comprising: an integer constraint requiring a first element of the attribute-change vector to have an integer value, an auto-increment constraint requiring a second element of the attribute-change vector to increase over a time period, the time period defined by a first time value associated with the first point and a second time value associated with the second point, a time constraint preventing a third element of the attribute-change vector from changing over the time period, or an autoencoder constraint applied to the sum of the input attribute vector and the attribute-change vector. 6 . The method of claim 1 , wherein generating the recommendation comprises: generating explanatory data indicating an impact of each value in the attribute-change vector on modifying the first value of the risk assessment score to the target value of the risk assessment score. 7 . A non-transitory computer-readable storage medium having program code that is executable by a processor device to cause a computing device to perform operations, the operations comprising: receiving, from a user device, a request for a recommendation for modifying a first value of a risk assessment score computed from input attribute values of an entity associated with the user device to a target value of the risk assessment score, the risk assessment score used to control access by a computing device associated with the entity to an interactive computing environment hosted by a host system, wherein the host system is configured to present a first type of interactive user experience to a first type of user group associated with the first value of the risk assessment score and present to a second type of interactive user experience to a second type of user group associated with the target value of the risk assessment score; computing an attribute-change vector indicating a path from (a) a first point that corresponds to the first value of the risk assessment score to (b) a second point that corresponds to the target value of the risk assessment score, wherein computing the attribute-change vector comprises: determining a requirement on movement from the first point to the second point, and selecting the attribute-change vector that complies with the requirement; generating, using the computed attribute-change vector, the recommendation; and transmitting, to the user device, the recommendation in response to the request for the recommendation for use in improving the first value of the risk assessment score to the target value of the risk assessment score which causes the host system to modify a functionality of an online interface by rearranging a layout of the online interface to switch from presenting the first type of interactive user experience to presenting the second type of interactive user experience. 8 . The non-transitory computer-readable storage medium of claim 7 , wherein the operations further comprise: determining the target value of the risk assessment score by applying a risk assessment function to a sum of an input attribute vector having the input attribute values of the entity; updating the input attribute vector by adding the attribute-change vector to the input attribute vector; assigning the updated input attribute vector to a second associated user group based on a similarity measure between the second associated user group and a second input point defined by the updated input attribute vector; and computing a second attribute-change vector indicating a second path from (a) the second point to (b) a third point in an m-dimensional space and that corresponds to a third value of the risk assessment score, wherein applying the risk assessment function to a sum of the updated input attribute vector and the second attribute-change vector outputs the third value of the risk assessment score, wherein computing the second attribute-change vector comprises: determining, based on statistics computed from the second associated user group to which the updated input attribute vector is assigned, a second requirement on movement from the second point to the third point, and selecting the second attribute-change vector that complies with the second requirement, wherein the recommendation is generated further using the second attribute-change vector. 9 . The non-transitory computer-readable storage medium of claim 7 , wherein the path complying with the requirement comprises the path being a shortest path along a surface between the first point and the second point in m-dimensional

Assignees

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Classifications

  • modifying the architecture, e.g. adding, deleting or silencing nodes or connections · CPC title

  • Supervised learning · CPC title

  • Feedforward networks · CPC title

  • Auto-encoder networks; Encoder-decoder networks · CPC title

  • Credit; Loans; Processing thereof · CPC title

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What does patent US2025232241A1 cover?
Systems and methods for automated path-based recommendation for risk mitigation are provided. An entity assessment server, responsive to a request for a recommendation for modifying a current risk assessment score of an entity to a target risk assessment score, accesses an input attribute vector for the entity and clusters of entities defined by historical attribute vectors. The entity assessme…
Who is the assignee on this patent?
Equifax Inc
What technology area does this patent fall under?
Primary CPC classification G06Q10/0635. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Jul 17 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).